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  • Colloquium on Digital Transformation Science

  • August 13, 3 pm CT

    Predictive and Prescriptive Analytics for the COVID-19 Pandemic

    Dimitris Bertsimas, Boeing Professor of Operations Research and Associate Dean of Business Analytics, MIT

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    The COVID-19 pandemic creates unprecedented challenges for healthcare providers and policy makers. How to triage patients when healthcare resources are limited? Whom to test? And how to design social distancing policies to contain the disease and its socioeconomic impact? Dimitris Bertsimas and Alexandre Jacquillat of MIT Sloan School of Management believe that analytics can provide an answer and have collected data from clinical studies, case counts, and hospital collaborations at www.covidanalytics.io. This colloquium will present their epidemiological model of the disease’s dynamics, a machine-learning model of mortality risk, and a resource allocation model. It will address: How can we predict admissions in intensive care units using machine learning? How does COVID-19 impact different demographic and socioeconomic populations? How does mobility impact the disease’s spread? How to optimize social distancing policies? How to augment COVID-19 tests with data-driven warnings that identify high-risk subjects? Bertsimas will present a new machine learning model for predicting being COVID-positive (https://covidanalytics.io/infection_calculator) and mortality (https://covidanalytics.io/mortality_calculator) using data from over 40 hospitals around the world, along with high-performance computing (using the C3 AI Suite), and advanced machine learning and artificial intelligence. He will summarize his research group’s end-to-end ML/AI methods, spanning epidemiological modeling (to model the disease’s spread), machine learning (to predict ICU admissions and test results), causal inference (to investigate disparities across populations), and optimal control (to support social distancing guidelines), as well as a new optimization model for allocating vaccines to minimize deaths.


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